There are several blogs out there explaining various architectures and approaches in Deep Learning. Some of these are very impressive and explain extensive research in simple language. The aim of this section is a bit different.

It is my observation that while blogs and papers appeal to different groups of people with different interests and explanations, there is quite an uphill climb when we think about transitioning from reading the blog to understanding the paper. In this section, however, we are going to take a paper and tear it down and analyze it. More than an explanation it explains the process in which I or any the concerned author of the explanation inferred the paper and drew conclusions and interests.

The blogs in this section shall not be categorized or ordered and shall be independent, discrete posts. Any complaint regarding an inference drawn or a comparison made or a mathematical error is most welcome and appreciated. Please send them here as GitHub Issues.